Abstract B27: Modeling the impact of miR-200s on mammary tumor initiation and progression in vitro and in vivo
Bibliographic record
Abstract
Abstract MicroRNAs (miRNAs) are small, noncoding RNAs that regulate mRNA translation through inhibiting the translation of mRNAs into proteins or through degrading mRNAs. Each miRNA potentially targets hundreds of mRNAs, and thus an individual miRNA can regulate entire gene networks. The miR-200 family consists of 5 miRNAs (miR-141, miR-200a, miR-200b, miR-200c, miR-429) organized into two clusters: the miR-200c/141 cluster and the miR-200b/200a/429 cluster. The miR-200s regulate a variety of cellular functions, with the best characterized being their ability to target mesenchymal transcription factors and thus maintain an epithelial phenotype. Given that miR-200s maintain an epithelial phenotype, we evaluated their role in mesenchymal mammary tumors. All five miR-200s were expressed at significantly lower levels in the murine mesenchymal mammary tumor cell line RJ423 and the human mesenchymal breast cancer cell line MDA-MB-231 compared to epithelial tumor cell lines. To evaluate the function of miR-200s, the miR-200c/141 and miR-200b/200a/429 clusters were re-expressed in the mesenchymal mammary tumors. Re-expression of the miR-200c/141 cluster partially restored an epithelial phenotype in MDA-MB-231 cells while the miR-200b/200a/429 cluster partially restored an epithelial phenotype in RJ423 cells. Re-expression of the miR-200c/141 cluster in MDA-MB-231 cells and re-expression of the miR-200b/200a/429 cluster in RJ423 cells significantly suppressed tumor growth following intramammary injection and altered the tumor microenvironment. To identify genes regulated by miR-200 expression, RNA sequencing was performed on control and miR-200 re-expressing cells grown in 2D culture and following intramammary injection. Interestingly, the in vivo environment dramatically altered the gene repertoire regulated by the miR-200s. Hierarchical clustering revealed that alterations in gene expression induced by miR-200 re-expression in vitro poorly correlated with the alterations in gene expression induced by miR-200 in vivo. Since miR-200 re-expression significantly decreased tumor growth in vivo, a transgenic model was used to determine whether miR-200s could also impact tumor initiation. Using doxycycline-inducible miR-200 expression in combination with the mammary tumor oncogene, IGF-IR, we found that overexpression of the miR-200b/200a/429 cluster dramatically reduced mammary tumor incidence (100% vs. 19%). These data show the potent impact miR-200s have on mammary tumorigenesis and that gene expression profiling of 2D cultures is a poor predictor of genes regulated by miR-200s in vivo. Citation Format: Katrina L. Watson, Kaitlyn Simpson, Majesta Roth, Courtney Martin, Garret Conquer-Van Heumen, Roger A. Moorehead. Modeling the impact of miR-200s on mammary tumor initiation and progression in vitro and in vivo [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr B27.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".